Knowledge sharing and yahoo answers: everyone knows something

By Lada A. Adamic, Jun Zhang, Eytan Bakshy, Mark S. Ackerman. The Web Conference, 2008

854 citations recorded by the source corpus.

Subfields: Communication, Computer Science Applications, Information Systems

View Paper: https://www.semanticscholar.org/paper/63f85ba163a16e4f80125bb627bc68a2153ad332

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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Citations in the corpus

Finding social roles in Wikipedia (2011, background): “social roles in online communities [2], [29].”
The labor economics of paid crowdsourcing (2010, neutral): “Crowdsourcing projects have used a variety of inducements, including entertainment [21], information [1, 13], and the chance to be altruistic and win attention from others [12].”
All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement (2015, methodology): “the average of the values from 5 windows of 10 posts. We also use the index of the window with the largest value and the smallest value as features, following [9]. All features are linearly scaled to [0;1] based on training data. Experiment protocol. In both tasks, we perform 30 randomized trials. I”
Analyzing (social media) networks with NodeXL (2009, background): “[1] illustrate the value of social network analysis for understanding the social connections within question and answer discussions in the Yahoo! Answers system.”
Learning to recognize reliable users and content in social media with coupled mutual reinforcement (2009, background): ““Authoritative” users may provide poor answers, and “poor” users may occasionally provide excellent answers [2, 1].”
A new space for comparing graphs (2014, background): “ed matter physics group, or Astro physics group. This is a speciﬁc version of a more general problem that arises in social media: “how audiences differ with respect to their social graph structure ?” [1]. For better insight into performance, we break the problem class-wise into 4 different classiﬁca”
Lurking? cyclopaths?: a quantitative lifecycle analysis of user behavior in a geowiki (2010, background): “One prominent line of research seeks to assign users to different interaction roles, often throu gh applying social network analysis [1, 7, 30].”
How do programmers ask and answer questions on the web?: NIER track (2011, background): “Adamic et al. [1] found that users who focused on certain areas of expertise often got the best ratings.”
Uncovering social spammers: social honeypots + machine learning (2010, background): “These social systems have attracted a tremendous amount of media and research interest [1, 10, 18].”
Causal discovery in social media using quasi-experimental designs (2010, background): “Researchers have tried to identify high-quality content in social media [2], and to identify attributes that predict answer quality in question and answer platforms [1, 9].”
Identifying Purchase Intent from Social Posts (2014, background): “Answers (YA) is a large and diverse Q&A forum (Adamic et al. 2008), acting not only as a medium for sharing technical knowledge, but also as a place where one can seek advice and gather opinions.”
What are developers talking about? An analysis of topics and trends in Stack Overflow (2014, background): “Adamic et al. (2008) also analyze Yahoo! Answers to cluster the top-level categories into three broader categories using both content and user interactions.”